In Proceedings of the ACM Conference on Human Factors in Computing Systems, CHI 2016.

5 things you didn't know about how you type

With just 5 fingers you can be as fast as somebody using all 10.

Don't worry if you never took a typing course. Those who did are not necessarily faster than you.

You could type without looking at your fingers, even if you never learned the touch typing system.

Your two hands move very differently when typing.

There are many strategies between "hunt-and-peck" and touch typing. In fact, we all type very differently.

Abstract

This paper revisits the present understanding of typing, which
originates mostly from studies of trained typists using the ten-
finger touch typing system. Our goal is to characterise the
majority of present-day users who are untrained and employ
diverse, self-taught techniques. In a transcription task, we
compare self-taught typists and those that took a touch typing
course. We report several differences in performance, gaze
deployment and movement strategies. The most surprising
finding is that self-taught typists can achieve performance
levels comparable with touch typists, even when using fewer
fingers. Motion capture data exposes 3 predictors of high
performance: 1) unambiguous mapping (a letter is consistently
pressed by the same finger), 2) active preparation of upcoming
keystrokes, and 3) minimal global hand motion. We release
an extensive dataset on everyday typing behavior.

Materials

Note: All images and videos can be downloaded in high resolution and used as press material.

Frequently Asked Questions

What is the touch typing system?
In the touch typing system, every finger is assigned to one or two columns of the keyboard.
All fingers are placed on their home position in the middle row and only move
up or down towards their respective keys. Therefore the hands are kept static on one position and it is possible to quickly learn how to type without looking at the keyboard.
However, learning to efficiently type with all 10 fingers requires many hours of deliberate practice.

How fast do I type?
To find out your typing speed, you can take a typing test online, such as this one ,
where you have to type random words for one minute. The speed is given in "words per minute", where one word is defined to be 5 characters long.

How can I get fast at typing, without learning to touch type?
We have not yet developed new training methods for typing. However, we found, that using more fingers doesn't make you faster.
Instead, we found a range of other factors that influence your performance.
If you do not want to spend many hours to learn how to efficiently use the touch typing system, you could try to remember the following

Keep your hands static. Move only your fingers towards the keys and try to keep the palms of your hands fixed on one position.

Look at the screen. You'll be surprised how well you can type without looking at your fingers.

Prepare upcoming keystrokes. Start with special keys, such as Shift, Backspace, or Enter, and move the unused fingers ealier.

What typing strategies did you find?

We found 4 different kind of strategies for the left hand and 6 for the right hand, by clustering the finger-to-key mapping.
They are shown in the image above and ordered by complexity.
From using mainly the Index or Middle finger of a hand, to more complex strategies with multiple fingers, up to the touch typing system. However, the strategy does not
determine the typing speed.

In which language did your participants type?
In order to observe the well practiced movement strategies of typing, we asked people to type in the language they use every day. This study was conducted in the Aalto University in Helsinki, Finnland.
Thus, the most common language for people was English or Finnish. Although the two languages are very different, our findings apply for both of them, and we could not find any
statistically significant differences in their performance or accuracy.

Why do we all type differently?
If you have never learned the touch typing system, you are, what we call, a self-taught typist. Your typing strategy has developed over the years of computer usage and probably adapted
to the tasks that you frequently do. This may not necessarily be typing.
For example, consider somebody that spends many hours playing computer games. When gaming, the fingers of their left hand are placed on the keys: Shift-A-W-D-Space, the right hand is on the mouse.
When switching to a chat window, they may keep this hand posture and adapt their typing strategy accordingly.

Did you find differences between men and women?
We looked at the typing behavior of 17 female and 13 male participants. Using the same statistical tests as described in the paper, we tested for statistically significant differences between the two groups.
We could not find any differences for any of the factors that we investigated (speed, accuracy, number of used fingers, etc. ) with 2 exceptions: on average, men typed random material about 7 wpm faster than women and
reported to use their computer about 15h more per week.

Are you saying that learning to touch type is useless?
No. Learning the touch typing system is still the best known way to get to very high typing speed. All world records have been achieved using that system. However, to get to a level, comparable to the fast typists in this study,
the touch typing system requires several hundred hours of deliberate(!) practice. In contrast, the self-taught techniques studied here, emerged from the daily use of computer keyboards
and were not intentionally practiced. If you want to consistently type sentences over 100 words per minute, learn the touch typing system. However, this system is less beneficial for other tasks, such as gaming, programming or media editing.
We still need to find a better strategy tailored to the needs of modern keyboard usage. In the mean time, your self-taught strategy may be the best compromise and you should rather practice the things mentioned above, instead of relearning
which finger presses which key.

Contact

This project has received funding from the Academy of Finland project COMPUTED and the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation
programme (grant agreement No 637991).